{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from deeptables.models import deeptable, deepnets\n",
    "from deeptables.datasets import dsutils\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = dsutils.load_bank()\n",
    "df.drop(['id'], axis=1, inplace=True)\n",
    "df_train, df_test = train_test_split(df, test_size=0.2, random_state=42)\n",
    "y = df_train.pop('y')\n",
    "y_test = df_test.pop('y')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 训练模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2 class detected, {'yes', 'no'}, so inferred as a [binary classification] task\n",
      "Preparing features taken 0.047048330307006836s\n",
      "Imputation taken 0.3113720417022705s\n",
      "Categorical encoding taken 0.5116350650787354s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/jack/opt/anaconda3/envs/tf_2_0/lib/python3.7/site-packages/sklearn/preprocessing/_discretization.py:202: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 0 are removed. Consider decreasing the number of bins.\n",
      "  'decreasing the number of bins.' % jj)\n",
      "/Users/jack/opt/anaconda3/envs/tf_2_0/lib/python3.7/site-packages/sklearn/preprocessing/_discretization.py:202: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 0 are removed. Consider decreasing the number of bins.\n",
      "  'decreasing the number of bins.' % jj)\n",
      "/Users/jack/opt/anaconda3/envs/tf_2_0/lib/python3.7/site-packages/sklearn/preprocessing/_discretization.py:202: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 0 are removed. Consider decreasing the number of bins.\n",
      "  'decreasing the number of bins.' % jj)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Discretization taken 0.25472283363342285s\n",
      "Injected a callback [EarlyStopping]. monitor:val_AUC, patience:1, mode:max\n",
      ">>>>>>>>>>>>>>>>>>>>>> Model Desc <<<<<<<<<<<<<<<<<<<<<<< \n",
      "---------------------------------------------------------\n",
      "inputs:\n",
      "---------------------------------------------------------\n",
      "['all_categorical_vars: (16)', 'input_continuous_all: (7)']\n",
      "---------------------------------------------------------\n",
      "embeddings:\n",
      "---------------------------------------------------------\n",
      "input_dims: [14, 5, 6, 4, 4, 4, 5, 14, 6, 5, 9, 4, 7, 4, 6, 4]\n",
      "output_dims: [4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4]\n",
      "dropout: 0.3\n",
      "---------------------------------------------------------\n",
      "dense: dropout: 0\n",
      "batch_normalization: False\n",
      "---------------------------------------------------------\n",
      "concat_embed_dense: shape: (None, 71)\n",
      "---------------------------------------------------------\n",
      "nets: ['dnn_nets', 'linear', 'fm_nets']\n",
      "---------------------------------------------------------\n",
      "dnn: input_shape (None, 71), output_shape (None, 64)\n",
      "linear: input_shape (None, 23), output_shape (None, 1)\n",
      "fm: input_shape (None, 16, 4), output_shape (None, 1)\n",
      "---------------------------------------------------------\n",
      "stacking_op: add\n",
      "---------------------------------------------------------\n",
      "output: activation: sigmoid, output_shape: (None, 1), use_bias: True\n",
      "loss: binary_crossentropy\n",
      "optimizer: Adam\n",
      "---------------------------------------------------------\n",
      "\n",
      "Train on 69442 samples, validate on 17361 samples\n",
      "Epoch 1/10\n",
      "69442/69442 [==============================] - 28s 406us/sample - loss: 29.4756 - AUC: 0.6428 - val_loss: 0.7646 - val_AUC: 0.7831\n",
      "Epoch 2/10\n",
      "69442/69442 [==============================] - 16s 237us/sample - loss: 0.4822 - AUC: 0.8203 - val_loss: 0.2461 - val_AUC: 0.9134\n",
      "Epoch 3/10\n",
      "69442/69442 [==============================] - 18s 252us/sample - loss: 0.2911 - AUC: 0.8759 - val_loss: 0.2124 - val_AUC: 0.9330\n",
      "Epoch 4/10\n",
      "69248/69442 [============================>.] - ETA: 0s - loss: 0.2547 - AUC: 0.8957Restoring model weights from the end of the best epoch.\n",
      "69442/69442 [==============================] - 18s 257us/sample - loss: 0.2546 - AUC: 0.8958 - val_loss: 0.2337 - val_AUC: 0.9325\n",
      "Epoch 00004: early stopping\n",
      "Model has been saved to:dt_output/dt_20201019 132136_dnn_nets_linear_fm_nets/dnn_nets+linear+fm_nets.h5\n"
     ]
    }
   ],
   "source": [
    "config = deeptable.ModelConfig(nets=deepnets.DeepFM, auto_discrete=True, metrics=['AUC'])\n",
    "dt = deeptable.DeepTable(config=config)\n",
    "\n",
    "model, history = dt.fit(df_train, y, epochs=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/jack/opt/anaconda3/envs/tf_2_0/lib/python3.7/site-packages/sklearn/utils/validation.py:72: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
      "  return f(**kwargs)\n"
     ]
    }
   ],
   "source": [
    "proba = dt.predict_proba(df_test)\n",
    "preds = dt.predict(df_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#model.model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 模型评估"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "result = dt.evaluate(df_test,y_test, batch_size=512, verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'loss': 0.22103416146668886, 'auc': 0.930402}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 输出网络架构"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from tensorflow.keras.utils import plot_model\n",
    "plot_model(model.model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 分析训练数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'loss': [29.475638984984947, 0.48223958303954745, 0.2910911392523853, 0.25459402107185786], 'auc': [0.6427965, 0.8202702, 0.8759316, 0.8958188], 'val_loss': [0.7646228752270264, 0.24609174191768074, 0.21236652380596774, 0.23365315741557732], 'val_auc': [0.7830583, 0.9134, 0.93301135, 0.93246216]}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "history.history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1a4daf3d10>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history.history['AUC'])\n",
    "plt.plot(history.history['val_AUC'])\n",
    "plt.legend(['train', 'val'], loc='upper left') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1a4fabc7d0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history.history['loss'],label='loss')\n",
    "plt.plot(history.history['val_loss'])\n",
    "plt.legend(['train', 'val'], loc='upper right') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
